This is an R Markdown presentation, created with knitr output set to html presentation.

The presentation includes plotly interactive graphics.

The dataset is taken from the final premier league tables for seasons 1995-96 through to 2017-18. Additional variables have been encoded, including

• How the team fared compared to the previous season and the change between that season and the one before
• Whether a manager was sacked during the season
• How many days the current manager has been in post

This code selects all the teams that finished at least 7 places higher in the previous season than the one before and plots these against the relative position this season compared to last. Teams that were promoted are not considered.

Consequently, teams above the black line continued to improve the third season, whereas teams below regressed. The bottom right portion of the plot shows teams that improved significantly the year before but came crashing back down the next season.

g <- ggplot(all_standings[all_standings$penultimate > 7 & all_standings$penultimate != 
    23, ], aes(x = penultimate, y = pos_this_last_diff, col = team)) + 
    geom_point() + geom_hline(yintercept = 0) + geom_text(aes(label = ifelse(penultimate > 
    13 | pos_this_last_diff > 5, as.character(team), ""), hjust = 0.8, 
    vjust = -0.5))

This plot can be made interactive using ggplotly() to convert a ggplot object into a plotly object

• Since plotly allows navigation around the plot, we can include more data points and allow the user to zoom in.

• Since identification of teams is possible with the mouse pointer, we can remove the labels and instead colour code by type - this allows identification of which teams were relegated qualified for europe etc.

• Shape of marker determines whether a new manager is in post this season

• Size of marker denotes how long a manager has been in post

First adjust x and y variables with minor noise in order to allow us to see overlapping points.

all_standings$last_this <- all_standings$pos_this_last_diff + 
    runif(460, -0.5, 0.5)
all_standings$penultimate_last <- all_standings$penultimate + 
    runif(460, -0.5, 0.5)
all_standings$new_mgr <- ifelse(all_standings$new_manager == 
    0, "No", "Yes")

g2 <- ggplot(all_standings[all_standings$penultimate != 23, ], 
    aes(x = penultimate_last, y = last_this, label = team, label2 = season, 
        label3 = penultimate, label4 = round(last_this), col = type, 
        shape = as.factor(new_mgr), size = manager_tenure)) + 
    geom_point() + geom_hline(yintercept = 0) + geom_vline(xintercept = 0) + 
    xlim(-1, 17) + labs(x = "penultimate season -> last season", 
    y = "last season -> this season", title = "Performance of teams who improved last season on the year before")

This plot can be made interactive using plotly as before.

The labels for the interactive marker can be passed to it but the legend is suppressed since plotly does not interpret complicated ggplot legends correctly.